o:3398 Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review en Introduction in 2017–2019 of the new EU legislation on official controls in food production allowed use of computer vision systems (CVSs) as complementary tools in meat inspection of bovines, pigs and poultry. A systematic literature review was performed to identify and analyse relevant articles reporting on the performances of CVSs used in abattoirs for ante- and post-mortem veterinary inspection and meat safety assurance, including systems for detecting carcass/organ contamination and lesions. In this review, 62 articles were identified and analysed. There were 35 articles reporting on CVS performance in the detection of carcass/organ lesions and 27 in the detection of carcass contamination. CVSs for broiler chicken, pig and bovine meat safety assurance were reported in 53, 5 and 4 articles, respectively. Not all developed CVSs were validated, and only three articles reported results from real-time evaluation of CVS performance in an abattoir vs performance of the official veterinarian. Most of the reported CVS performance measures (i.e., sensitivity and specificity) were > 80%. A high specificity in detecting lesions and carcass contamination (i.e., a low number of false positives) is of importance for the food business operator in order to minimise food waste, whereas a high sensitivity (i.e., a low number of false negatives) is required for production of wholesome and safe meat. At present, the existing CVSs developed for overall meat safety assurance of broiler chicken carcasses and organs demonstrate very high sensitivities but suboptimal specificities, indicating the need for further CVS development and optimisation. Computer vision, Imaging, Meat inspection, Meat safety assurance, Lesions, Carcass contamination 1552099 10.1016/j.foodcont.2023.109768 2023-11-28T12:32:32.546Z 44 yes 46 Marianne Sandberg National Food Institute, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review Sergio Ghidini Department of Food and Drug, University of Parma, Via del Taglio 10, 43126, Parma, Italy Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Lis Alban Department for Food Safety, Veterinary Issues and Risk Analysis, Danish Agriculture & Food Council, Agrofood Park 13, DK-8200, Aarhus N, Denmark Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Andrea Capobianco Dondona Farm4Trade s.r.l., Via IV Novembre, 66041, Atessa, Italy Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Bojan Blagojevic Department of Veterinary Medicine, Faculty of Agriculture, University of Novi Sad, Trg D. Obradovica 8, 21000, Novi Sad, Serbia Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Martijn Bouwknegt Vion Food Group, Boseind 15, 5281 RM, Boxtel, the Netherlands Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Len Lipman Department Population Health Sciences, Institute for Risk Assessment Sciences (IRAS), University of Utrecht, 3584, CM Utrecht, the Netherlands Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Jeppe Seidelin Dam Danish Technological Institute, Grønnegårdsvej 1, 2630, Taastrup, Denmark Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person Ivan Nastasijevic Institute of meat hygiene and technology person Dragan Antic Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Leahurst, Neston, CH64 7TE, United Kingdom Applications of computer vision systems for meat safety assurance in abattoirs: A systematic review person 2023-03-30 application/pdf 4074833 https://unilib.phaidrabg.rs/o:3398 no yes 16 70 1552253 71A01 Food Control 150 150 109786 Food Control journal homepage: www.elsevier.com/locate/foodcont Elsevier 2023-03-30